BUG: Allow IntervalIndex to be constructed from categorical data with appropriate dtype (pandas-dev#21254)

Author: jschendel

doc/source/whatsnew/v0.23.1.txt

@@ -85,6 +85,7 @@ Indexing
 - Bug in :meth:`Series.reset_index` where appropriate error was not raised with an invalid level name (:issue:`20925`)
 - Bug in :func:`interval_range` when ``start``/``periods`` or ``end``/``periods`` are specified with float ``start`` or ``end`` (:issue:`21161`)
 - Bug in :meth:`MultiIndex.set_names` where error raised for a ``MultiIndex`` with ``nlevels == 1`` (:issue:`21149`)
+- Bug in :class:`IntervalIndex` constructors where creating an ``IntervalIndex`` from categorical data was not fully supported (:issue:`21243`, issue:`21253`)
 -
 
 I/O

pandas/core/indexes/interval.py

@@ -112,6 +112,10 @@ def maybe_convert_platform_interval(values):
     -------
     array
     """
+    if is_categorical_dtype(values):
+        # GH 21243/21253
+        values = np.array(values)
+
     if isinstance(values, (list, tuple)) and len(values) == 0:
         # GH 19016
         # empty lists/tuples get object dtype by default, but this is not

pandas/tests/indexes/interval/test_construction.py

@@ -6,8 +6,9 @@
 
 from pandas import (
     Interval, IntervalIndex, Index, Int64Index, Float64Index, Categorical,
-    date_range, timedelta_range, period_range, notna)
+    CategoricalIndex, date_range, timedelta_range, period_range, notna)
 from pandas.compat import lzip
+from pandas.core.dtypes.common import is_categorical_dtype
 from pandas.core.dtypes.dtypes import IntervalDtype
 import pandas.core.common as com
 import pandas.util.testing as tm
@@ -111,6 +112,22 @@ def test_constructor_string(self, constructor, breaks):
         with tm.assert_raises_regex(TypeError, msg):
             constructor(**self.get_kwargs_from_breaks(breaks))
 
+    @pytest.mark.parametrize('cat_constructor', [
+        Categorical, CategoricalIndex])
+    def test_constructor_categorical_valid(self, constructor, cat_constructor):
+        # GH 21243/21253
+        if isinstance(constructor, partial) and constructor.func is Index:
+            # Index is defined to create CategoricalIndex from categorical data
+            pytest.skip()
+
+        breaks = np.arange(10, dtype='int64')
+        expected = IntervalIndex.from_breaks(breaks)
+
+        cat_breaks = cat_constructor(breaks)
+        result_kwargs = self.get_kwargs_from_breaks(cat_breaks)
+        result = constructor(**result_kwargs)
+        tm.assert_index_equal(result, expected)
+
     def test_generic_errors(self, constructor):
         # filler input data to be used when supplying invalid kwargs
         filler = self.get_kwargs_from_breaks(range(10))
@@ -238,6 +255,8 @@ def get_kwargs_from_breaks(self, breaks, closed='right'):
         tuples = lzip(breaks[:-1], breaks[1:])
         if isinstance(breaks, (list, tuple)):
             return {'data': tuples}
+        elif is_categorical_dtype(breaks):
+            return {'data': breaks._constructor(tuples)}
         return {'data': com._asarray_tuplesafe(tuples)}
 
     def test_constructor_errors(self):
@@ -286,6 +305,8 @@ def get_kwargs_from_breaks(self, breaks, closed='right'):
 
         if isinstance(breaks, list):
             return {'data': ivs}
+        elif is_categorical_dtype(breaks):
+            return {'data': breaks._constructor(ivs)}
         return {'data': np.array(ivs, dtype=object)}
 
     def test_generic_errors(self, constructor):